A Variable Occurrence-Centric Framework for Inconsistency Handling

Authors

  • Yakoub Salhi Univ. Artois, CNRS, CRIL, France

DOI:

https://doi.org/10.1609/aaai.v39i14.33661

Abstract

In this paper, we introduce a syntactic framework for analyzing and handling inconsistencies in propositional bases. Our approach focuses on examining the relationships between variable occurrences within conflicts. We propose two dual concepts: Minimal Inconsistency Relation (MIR) and Maximal Consistency Relation (MCR). Each MIR is a minimal equivalence relation on variable occurrences that results in inconsistency, while each MCR is a maximal equivalence relation designed to prevent inconsistency. Notably, MIRs capture conflicts overlooked by minimal inconsistent subsets. Using MCRs, we develop a series of non-explosive inference relations. The main strategy involves restoring consistency by modifying the propositional base according to each MCR, followed by employing the classical inference relation to derive conclusions. Additionally, we propose an unusual semantics that assigns truth values to variable occurrences instead of the variables themselves. The associated inference relations are established through Boolean interpretations compatible with the occurrence-based models.

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Published

2025-04-11

How to Cite

Salhi, Y. (2025). A Variable Occurrence-Centric Framework for Inconsistency Handling. Proceedings of the AAAI Conference on Artificial Intelligence, 39(14), 15143–15150. https://doi.org/10.1609/aaai.v39i14.33661

Issue

Section

AAAI Technical Track on Knowledge Representation and Reasoning